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\nData Science 🐍 Classification\n

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\n\nPublisher:\n\nAPMonitor\n\n\n
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\nClassification predicts discrete labels (outcomes) such as yes/no, True/False, or any number of discrete levels such as a letter from text recognition, or a word from speech recognition. There are two main methods for training...\nClassification predicts discrete labels (outcomes) such as yes/no, True/False, or any number of discrete levels such as a letter from text recognition, or a word from speech recognition. There are two main methods for training classifiers: unsupervised and supervised learning. The difference between the two is that unsupervised learning does not use labels while supervised learning uses labels to build the classifier. The goal of unsupervised learning is to cluster input features but without labels to guide the grouping.

Course Modules
1. Data Science 🐍 Course Overview
2. Data Science 🐍 Import / Export
3. Data Science 🐍 Analyze
4. Data Science 🐍 Visualize
5. Data Science 🐍 Prepare Data
6. Data Science 🐍 Regression
7. Data Science 🐍 Features
8. Data Science 🐍 Classification
9. Data Science 🐍 Interpolation
10. Data Science 🐍 Solve Equations
11. Data Science 🐍 Differential Equations
12. Data Science 🐍 Time Series
Data Science 🐍 Final Project

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Resource Details

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Curator Rating
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Educator Rating
Not yet Rated
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Media Length
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15:20
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Grade
10th - Higher Ed
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Subjects
STEM
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Media Type
Instructional Videos
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Source:
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\nAPMonitor.com\n\n
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Date
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2020
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Language
English
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Audiences
For Teacher Use
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Usage Permissions
Fine Print: Educational Use
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Additional Materials

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Concepts

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classification, data, faults, temperature
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Additional Tags

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machine learning, cluster, clustering, sklearn, introduction, classifier, supervised, unsupervised, neural network, logistic regression, spectral clustering, unsupervised learning, nearest neighbors, supervised learning, training set, data points, classification methods, labeled data, correct answer, training, answer, incorrect, simple, correct, line, classified, heater, true, talk, types, labels
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Classroom Considerations

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Best For: Explaining a topic
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Educator Ratings

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